(to appear):
Mitzlaff, F.; Benz, D.; Stumme, G. & Hotho, A.
(2010):
Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy.
In: Proceedings of the 21st ACM conference on Hypertext and hypermedia,
Toronto, Canada.
[Volltext]
[BibTeX][Endnote]
@inproceedings{mitzlaff2010visit,
author = {Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas},
title = {Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy},
booktitle = {Proceedings of the 21st ACM conference on Hypertext and hypermedia},
address = {Toronto, Canada},
year = {2010},
note = {(to appear)},
url = {http://www.kde.cs.uni-kassel.de/pub/pdf/mitzlaff2010visit.pdf},
keywords = {graph, social_links, social_network, myown, evidence_networks, 2010, analysis, user_relationships, itegpub}
}
%0 = inproceedings
%A = Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas
%B = Proceedings of the 21st ACM conference on Hypertext and hypermedia
%C = Toronto, Canada
%D = 2010
%T = Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy
%U = http://www.kde.cs.uni-kassel.de/pub/pdf/mitzlaff2010visit.pdf
Murata, T.
(2009):
Modularities for Bipartite Networks.
In: HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia,
New York, NY, USA.
[Kurzfassung] [BibTeX][Endnote]
Real-world relations are often represented as bipartite networks, such as paper-author networks and event-attendee networks. Extracting dense subnetworks (communities) from bipartite networks and evaluating their qualities are practically important research topics. As the attempts for evaluating divisions of bipartite networks, Guimera and Barber propose bipartite modularities. This paper discusses the properties of these bipartite modularities and proposes another bipartite modularity that allows one-to-many correspondence of communities of different vertex types. Preliminary experimental results for the bipartite modularities are also described.
@inproceedings{murata2009modularities,
author = {Murata, Tsuyoshi},
title = {Modularities for Bipartite Networks},
booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
publisher = {ACM},
address = {New York, NY, USA},
year = {2009},
keywords = {ht09, graph, bipartite},
abstract = {Real-world relations are often represented as bipartite networks, such as paper-author networks and event-attendee networks. Extracting dense subnetworks (communities) from bipartite networks and evaluating their qualities are practically important research topics. As the attempts for evaluating divisions of bipartite networks, Guimera and Barber propose bipartite modularities. This paper discusses the properties of these bipartite modularities and proposes another bipartite modularity that allows one-to-many correspondence of communities of different vertex types. Preliminary experimental results for the bipartite modularities are also described.}
}
%0 = inproceedings
%A = Murata, Tsuyoshi
%B = HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia
%C = New York, NY, USA
%D = 2009
%I = ACM
%T = Modularities for Bipartite Networks
Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.
(2006):
Information Retrieval in Folksonomies: Search and Ranking.
In: The Semantic Web: Research and Applications,
Heidelberg.
[Kurzfassung] [BibTeX][Endnote]
Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies,called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to findcommunities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.
@inproceedings{hotho2006information,
author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
title = {Information Retrieval in Folksonomies: Search and Ranking},
editor = {Sure, York and Domingue, John},
booktitle = {The Semantic Web: Research and Applications},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
address = {Heidelberg},
year = {2006},
volume = {4011},
pages = {411-426},
keywords = {2006, folkrank, folksonomy, graph, iccs_example, information, l3s, mining, ol_web2.0, pagerank, rank, ranking, retrieval, search, seminar2006, testttag, trias_example, webzu, widely_related},
abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies,called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to findcommunities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.}
}
%0 = inproceedings
%A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd
%B = The Semantic Web: Research and Applications
%C = Heidelberg
%D = 2006
%I = Springer
%T = Information Retrieval in Folksonomies: Search and Ranking